This paper aims to review the previously developed Computer-aided detection (CAD)
systems for mammogram screening because increasing death rate in women due to breast …

This paper presents a fully automated segmentation and classification scheme for
mammograms, based on breast density estimation and detection of asymmetry. First, image …

This work explores the design of mammography-based machine learning classifiers (MLC)
and proposes a new method to build MLC for breast cancer diagnosis. We massively …

Purpose Improving radiologists' performance in classification between malignant and
benign breast lesions is important to increase cancer detection sensitivity and reduce false …

OBJECTIVE: Localized texture analysis of breast tissue on mammograms is an issue of
major importance in mass characterization. However, in contrast to other mammographic …

Breast cancer continues to be a significant public health problem in the world. Early
detection is the key for improving breast cancer prognosis. Mammogram breast X-ray is …

Fast-paced mobile technology development has permitted augmented reality experiences to
be delivered on mobile pedestrian navigation context. The fact that the more prevalent of this …

Proposed system has been developed to extract the optimal features from the breast tumors
using Enhanced Cuckoo Search (ECS) and presented in this paper. The texture feature …

OBJECTIVE: A comprehensive signal analysis approach on the mammographic mass
boundary morphology is presented in this article. The purpose of this study is to identify …

Objectives This study aims to evaluate digital mammography (DM), digital breast
tomosynthesis (DBT), dynamic contrast-enhanced (DCE), and diffusion-weighted (DW) MRI …